SpikeShip: A method for fast, unsupervised discovery of high-dimensional neural spiking patterns.

ABSTRACT: Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences requires a suitable dissimilarity measure to spiking patterns, which can then be used for clustering and decoding. Here, we present a new dissimilarity measure based on optimal transport theory called SpikeShip, which compares multi-neuron spiking patterns based on all the relative spike-timing relationships among neurons. SpikeShip computes the optimal transport cost to make all the relative spike-timing relationships (across neurons) identical between two spiking patterns. We show that this transport cost can be decomposed into a temporal rigid translation term, which captures global latency shifts,

SUBMITTER: Sotomayor-Gomez B 

PROVIDER: S-EPMC10414626 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature